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One major question in molecular biology is whether the spatial distribution of observed molecules is random or organized in clusters. Indeed, this analysis gives information about molecules interactions and physical interplay with their environment. The standard tool for analyzing molecules distribution statistically is the Ripleys K function, which tests spatial randomness through the computation of its critical quantiles. However, quantiles computation is very cumbersome, hindering its use. Here, we present an analytical expression of these quantiles, leading to a fast and robust statistical test, and we derive the characteristic clusters size from the maxima of the Ripleys K function. Subsequently, we analyze the spatial organization of endocytic spots at the cell membrane and we report that clathrin spots are randomly distributed while clathrin-independent spots are organized in clusters with a radius of [Formula: see text], which suggests distinct physical mechanisms and cellular functions for each pathway.

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn’t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on µm-sized membrane regions in the micro-to-milli-second time range.

We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.

Institutions: CFEL, DESY, University of Hamburg, University of Hamburg.

Gas-phase molecular physics and physical chemistry experiments commonly use supersonic expansions through pulsed valves for the production of cold molecular beams. However, these beams often contain multiple conformers and clusters, even at low rotational temperatures. We present an experimental methodology that allows the spatial separation of these constituent parts of a molecular beam expansion. Using an electric deflector the beam is separated by its mass-to-dipole moment ratio, analogous to a bender or an electric sector mass spectrometer spatially dispersing charged molecules on the basis of their mass-to-charge ratio. This deflector exploits the Stark effect in an inhomogeneous electric field and allows the separation of individual species of polar neutral molecules and clusters. It furthermore allows the selection of the coldest part of a molecular beam, as low-energy rotational quantum states generally experience the largest deflection. Different structural isomers (conformers) of a species can be separated due to the different arrangement of functional groups, which leads to distinct dipole moments. These are exploited by the electrostatic deflector for the production of a conformationally pure sample from a molecular beam. Similarly, specific cluster stoichiometries can be selected, as the mass and dipole moment of a given cluster depends on the degree of solvation around the parent molecule. This allows experiments on specific cluster sizes and structures, enabling the systematic study of solvation of neutral molecules.

Protein-DNA interactions are at the heart of many fundamental cellular processes. For example, DNA replication, transcription, repair, and chromosome organization are governed by DNA-binding proteins that recognize specific DNA structures or sequences. In vitro experiments have helped to generate detailed models for the function of many types of DNA-binding proteins, yet, the exact mechanisms of these processes and their organization in the complex environment of the living cell remain far less understood. We recently introduced a method for quantifying DNA-repair activities in live Escherichia coli cells using Photoactivated Localization Microscopy (PALM) combined with single-molecule tracking. Our general approach identifies individual DNA-binding events by the change in the mobility of a single protein upon association with the chromosome. The fraction of bound molecules provides a direct quantitative measure for the protein activity and abundance of substrates or binding sites at the single-cell level. Here, we describe the concept of the method and demonstrate sample preparation, data acquisition, and data analysis procedures.

Institutions: University of Texas Medical Branch, University of Texas Medical Branch, University of Texas Medical Branch.

Cryo-electron microscopy (Cryo-EM)1 is a powerful approach to investigate the functional structure of proteins and complexes in a hydrated state and membrane environment2.
Coagulation Factor VIII (FVIII)3 is a multi-domain blood plasma glycoprotein. Defect or deficiency of FVIII is the cause for Hemophilia type A - a severe bleeding disorder. Upon proteolytic activation, FVIII binds to the serine protease Factor IXa on the negatively charged platelet membrane, which is critical for normal blood clotting4. Despite the pivotal role FVIII plays in coagulation, structural information for its membrane-bound state is incomplete5. Recombinant FVIII concentrate is the most effective drug against Hemophilia type A and commercially available FVIII can be expressed as human or porcine, both forming functional complexes with human Factor IXa6,7.
In this study we present a combination of Cryo-electron microscopy (Cryo-EM), lipid nanotechnology and structure analysis applied to resolve the membrane-bound structure of two highly homologous FVIII forms: human and porcine. The methodology developed in our laboratory to helically organize the two functional recombinant FVIII forms on negatively charged lipid nanotubes (LNT) is described. The representative results demonstrate that our approach is sufficiently sensitive to define the differences in the helical organization between the two highly homologous in sequence (86% sequence identity) proteins. Detailed protocols for the helical organization, Cryo-EM and electron tomography (ET) data acquisition are given. The two-dimensional (2D) and three-dimensional (3D) structure analysis applied to obtain the 3D reconstructions of human and porcine FVIII-LNT is discussed. The presented human and porcine FVIII-LNT structures show the potential of the proposed methodology to calculate the functional, membrane-bound organization of blood coagulation Factor VIII at high resolution.

In Situ SIMS and IR Spectroscopy of Well-defined Surfaces Prepared by Soft Landing of Mass-selected Ions

Authors: Grant E. Johnson, K. Don Dasitha Gunaratne, Julia Laskin.

Institutions: Pacific Northwest National Laboratory.

Soft landing of mass-selected ions onto surfaces is a powerful approach for the highly-controlled preparation of materials that are inaccessible using conventional synthesis techniques. Coupling soft landing with in situ characterization using secondary ion mass spectrometry (SIMS) and infrared reflection absorption spectroscopy (IRRAS) enables analysis of well-defined surfaces under clean vacuum conditions. The capabilities of three soft-landing instruments constructed in our laboratory are illustrated for the representative system of surface-bound organometallics prepared by soft landing of mass-selected ruthenium tris(bipyridine) dications, [Ru(bpy)3]2+ (bpy = bipyridine), onto carboxylic acid terminated self-assembled monolayer surfaces on gold (COOH-SAMs). In situ time-of-flight (TOF)-SIMS provides insight into the reactivity of the soft-landed ions. In addition, the kinetics of charge reduction, neutralization and desorption occurring on the COOH-SAM both during and after ion soft landing are studied using in situ Fourier transform ion cyclotron resonance (FT-ICR)-SIMS measurements. In situ IRRAS experiments provide insight into how the structure of organic ligands surrounding metal centers is perturbed through immobilization of organometallic ions on COOH-SAM surfaces by soft landing. Collectively, the three instruments provide complementary information about the chemical composition, reactivity and structure of well-defined species supported on surfaces.

Institutions: The Children's Hospital of Philadelphia, University of Pennsylvania.

In-stent restenosis presents a major complication of stent-based revascularization procedures widely used to re-establish blood flow through critically narrowed segments of coronary and peripheral arteries. Endovascular stents capable of tunable release of genes with anti-restenotic activity may present an alternative strategy to presently used drug-eluting stents. In order to attain clinical translation, gene-eluting stents must exhibit predictable kinetics of stent-immobilized gene vector release and site-specific transduction of vasculature, while avoiding an excessive inflammatory response typically associated with the polymer coatings used for physical entrapment of the vector. This paper describes a detailed methodology for coatless tethering of adenoviral gene vectors to stents based on a reversible binding of the adenoviral particles to polyallylamine bisphosphonate (PABT)-modified stainless steel surface via hydrolysable cross-linkers (HC). A family of bifunctional (amine- and thiol-reactive) HC with an average t1/2 of the in-chain ester hydrolysis ranging between 5 and 50 days were used to link the vector with the stent. The vector immobilization procedure is typically carried out within 9 hr and consists of several steps: 1) incubation of the metal samples in an aqueous solution of PABT (4 hr); 2) deprotection of thiol groups installed in PABT with tris(2-carboxyethyl) phosphine (20 min); 3) expansion of thiol reactive capacity of the metal surface by reacting the samples with polyethyleneimine derivatized with pyridyldithio (PDT) groups (2 hr); 4) conversion of PDT groups to thiols with dithiothreitol (10 min); 5) modification of adenoviruses with HC (1 hr); 6) purification of modified adenoviral particles by size-exclusion column chromatography (15 min) and 7) immobilization of thiol-reactive adenoviral particles on the thiolated steel surface (1 hr). This technique has wide potential applicability beyond stents, by facilitating surface engineering of bioprosthetic devices to enhance their biocompatibility through the substrate-mediated gene delivery to the cells interfacing the implanted foreign material.

Institutions: UCL Institute of Child Health, University College London.

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.
In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.

Many important signaling receptors are internalized through the well-studied process of clathrin-mediated endocytosis (CME). Traditional cell biological assays, measuring global changes in endocytosis, have identified over 30 known components participating in CME, and biochemical studies have generated an interaction map of many of these components. It is becoming increasingly clear, however, that CME is a highly dynamic process whose regulation is complex and delicate. In this manuscript, we describe the use of Total Internal Reflection Fluorescence (TIRF) microscopy to directly visualize the dynamics of components of the clathrin-mediated endocytic machinery, in real time in living cells, at the level of individual events that mediate this process. This approach is essential to elucidate the subtle changes that can alter endocytosis without globally blocking it, as is seen with physiological regulation. We will focus on using this technique to analyze an area of emerging interest, the role of cargo composition in modulating the dynamics of distinct clathrin-coated pits (CCPs). This protocol is compatible with a variety of widely available fluorescence probes, and may be applied to visualizing the dynamics of many cargo molecules that are internalized from the cell surface.

A wide range of methods are currently available for determining the dissociation constant between a protein and interacting small molecules. However, most of these require access to specialist equipment, and often require a degree of expertise to effectively establish reliable experiments and analyze data. Differential scanning fluorimetry (DSF) is being increasingly used as a robust method for initial screening of proteins for interacting small molecules, either for identifying physiological partners or for hit discovery. This technique has the advantage that it requires only a PCR machine suitable for quantitative PCR, and so suitable instrumentation is available in most institutions; an excellent range of protocols are already available; and there are strong precedents in the literature for multiple uses of the method. Past work has proposed several means of calculating dissociation constants from DSF data, but these are mathematically demanding. Here, we demonstrate a method for estimating dissociation constants from a moderate amount of DSF experimental data. These data can typically be collected and analyzed within a single day. We demonstrate how different models can be used to fit data collected from simple binding events, and where cooperative binding or independent binding sites are present. Finally, we present an example of data analysis in a case where standard models do not apply. These methods are illustrated with data collected on commercially available control proteins, and two proteins from our research program. Overall, our method provides a straightforward way for researchers to rapidly gain further insight into protein-ligand interactions using DSF.

Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.

In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.

Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.

Institutions: The Babraham Institute, The Babraham Institute, University of Cambridge .

3D DNA FISH has become a major tool for analyzing three-dimensional organization of the nucleus, and several variations of the technique have been published. In this article we describe a protocol which has been optimized for robustness, reproducibility, and ease of use. Brightly fluorescent directly labeled probes are generated by nick-translation with amino-allyldUTP followed by chemical coupling of the dye. 3D DNA FISH is performed using a freeze-thaw step for cell permeabilization and a heating step for simultaneous denaturation of probe and nuclear DNA. The protocol is applicable to a range of cell types and a variety of probes (BACs, plasmids, fosmids, or Whole Chromosome Paints) and allows for high-throughput automated imaging. With this method we routinely investigate nuclear localization of up to three chromosomal regions.

Carbon-based nanomaterials, like carbon nanotubes (CNTs), belong to this type of nanoparticles which are very difficult to discriminate from carbon-rich cell structures and de facto there is still no quantitative method to assess their distribution at cell and tissue levels. What we propose here is an innovative method allowing the detection and quantification of CNTs in cells using a multispectral imaging flow cytometer (ImageStream, Amnis). This newly developed device integrates both a high-throughput of cells and high resolution imaging, providing thus images for each cell directly in flow and therefore statistically relevant image analysis. Each cell image is acquired on bright-field (BF), dark-field (DF), and fluorescent channels, giving access respectively to the level and the distribution of light absorption, light scattered and fluorescence for each cell. The analysis consists then in a pixel-by-pixel comparison of each image, of the 7,000-10,000 cells acquired for each condition of the experiment. Localization and quantification of CNTs is made possible thanks to some particular intrinsic properties of CNTs: strong light absorbance and scattering; indeed CNTs appear as strongly absorbed dark spots on BF and bright spots on DF with a precise colocalization.
This methodology could have a considerable impact on studies about interactions between nanomaterials and cells given that this protocol is applicable for a large range of nanomaterials, insofar as they are capable of absorbing (and/or scattering) strongly enough the light.

Institutions: State University of New York at Stony Brook, NED University of Engineering and Technology.

Here, we present a simple and rapid protocol to detect and assess the extent of cell-to-cell macromolecular transport in planta. In this protocol, a fluorescently tagged-protein of interest is transiently expressed in plant tissue following biolistic delivery of its encoding DNA construct. The intra- and intercellular distribution of the tagged protein is then analyzed by confocal microscopy. We describe this technology in detail, providing step-by-step protocols to assay and evaluate the extent of symplastic protein transport in three plant species, Arabidopsis thaliana, Nicotiana benthamiana and N. tabacum (tobacco).

A major endocytic pathway initiates with the formation of clathrin-coated vesicles (CCVs) that transport cargo from the cell surface to endosomes1-6. CCVs are distinguished by a polyhedral lattice of clathrin that coats the vesicle membrane and serves as a mechanical scaffold. Clathrin coats are assembled during vesicle formation from individual clathrin triskelia , the soluble form of clathrin composed of three heavy and three light chain subunits7,8. Because the triskelion does not have the ability to bind to the membrane directly, clathrin-binding adaptors are critical to link the forming clathrin lattice to the membrane through association with lipids and/or membrane proteins9. Adaptors also package transmembrane protein cargo, such as receptors, and can interact with each other and with other components of the CCV formation machinery9.
Over twenty clathrin adaptors have been described, several are involved in clathrin mediated endocytosis and others localize to the trans Golgi network or endosomes9. With the exception of HIP1R (yeast Sla2p), all known clathrin adaptors bind to the N-terminal -propeller domain of the clathrin heavy chain9. Clathrin adaptors are modular proteins consisting of folded domains connected by unstructured flexible linkers. Within these linker regions, short binding motifs mediate interactions with the clathrin N-terminal domain or other components of the vesicle formation machinery9. Two distinct clathrin-binding motifs have been defined: the clathrin-box and the W-box9. The consensus clathrin-box sequence was originally defined as L[L/I][D/E/N][L/F][D/E]10 but variants have been subsequently discovered11. The W-box conforms to the sequence PWxxW (where x is any residue).
Sla1p (Synthetic Lethal with Actin binding protein-1) was originally identified as an actin associated protein and is necessary for normal actin cytoskeleton structure and dynamics at endocytic sites in yeast cells12. Sla1p also binds the NPFxD endocytic sorting signal and is critical for endocytosis of cargo bearing the NPFxD signal13,14. More recently, Sla1p was demonstrated to bind clathrin through a motif similar to the clathrin box, LLDLQ, termed a variant clathrin-box (vCB), and to function as an endocytic clathrin adaptor15. In addition, Sla1p has become a widely used marker for the endocytic coat in live cell fluorescence microscopy studies16. Here we use Sla1p as a model to describe approaches for adaptor-clathrin interaction studies. We focus on live cell fluorescence microscopy, GST-pull down, and co-immunoprecipitation methods.

Biofilms are highly dynamic, organized and structured communities of microbial cells enmeshed in an extracellular matrix of variable density and composition 1, 2. In general, biofilms develop from initial microbial attachment on a surface followed by formation of cell clusters (or microcolonies) and further development and stabilization of the microcolonies, which occur in a complex extracellular matrix. The majority of biofilm matrices harbor exopolysaccharides (EPS), and dental biofilms are no exception; especially those associated with caries disease, which are mostly mediated by mutans streptococci 3. The EPS are synthesized by microorganisms (S. mutans, a key contributor) by means of extracellular enzymes, such as glucosyltransferases using sucrose primarily as substrate 3.
Studies of biofilms formed on tooth surfaces are particularly challenging owing to their constant exposure to environmental challenges associated with complex diet-host-microbial interactions occurring in the oral cavity. Better understanding of the dynamic changes of the structural organization and composition of the matrix, physiology and transcriptome/proteome profile of biofilm-cells in response to these complex interactions would further advance the current knowledge of how oral biofilms modulate pathogenicity. Therefore, we have developed an analytical tool-box to facilitate biofilm analysis at structural, biochemical and molecular levels by combining commonly available and novel techniques with custom-made software for data analysis. Standard analytical (colorimetric assays, RT-qPCR and microarrays) and novel fluorescence techniques (for simultaneous labeling of bacteria and EPS) were integrated with specific software for data analysis to address the complex nature of oral biofilm research.
The tool-box is comprised of 4 distinct but interconnected steps (Figure 1): 1) Bioassays, 2) Raw Data Input, 3) Data Processing, and 4) Data Analysis. We used our in vitro biofilm model and specific experimental conditions to demonstrate the usefulness and flexibility of the tool-box. The biofilm model is simple, reproducible and multiple replicates of a single experiment can be done simultaneously 4, 5. Moreover, it allows temporal evaluation, inclusion of various microbial species 5 and assessment of the effects of distinct experimental conditions (e.g. treatments 6; comparison of knockout mutants vs. parental strain 5; carbohydrates availability 7). Here, we describe two specific components of the tool-box, including (i) new software for microarray data mining/organization (MDV) and fluorescence imaging analysis (DUOSTAT), and (ii) in situ EPS-labeling. We also provide an experimental case showing how the tool-box can assist with biofilms analysis, data organization, integration and interpretation.

Our goal is to obtain a comprehensive description of molecular processes occurring at cellular membranes in different biological functions. We aim at characterizing the complex organization and dynamics of the plasma membrane at single-molecule level, by developing analytic tools dedicated to Single-Particle Tracking (SPT) at high density: Multiple-Target Tracing (MTT)1. Single-molecule videomicroscopy, offering millisecond and nanometric resolution1-11, allows a detailed representation of membrane organization12-14 by accurately mapping descriptors such as cell receptors localization, mobility, confinement or interactions.
We revisited SPT, both experimentally and algorithmically. Experimental aspects included optimizing setup and cell labeling, with a particular emphasis on reaching the highest possible labeling density, in order to provide a dynamic snapshot of molecular dynamics as it occurs within the membrane. Algorithmic issues concerned each step used for rebuilding trajectories: peaks detection, estimation and reconnection, addressed by specific tools from image analysis15,16. Implementing deflation after detection allows rescuing peaks initially hidden by neighboring, stronger peaks. Of note, improving detection directly impacts reconnection, by reducing gaps within trajectories. Performances have been evaluated using Monte-Carlo simulations for various labeling density and noise values, which typically represent the two major limitations for parallel measurements at high spatiotemporal resolution.
The nanometric accuracy17 obtained for single molecules, using either successive on/off photoswitching or non-linear optics, can deliver exhaustive observations. This is the basis of nanoscopy methods17 such as STORM18, PALM19,20, RESOLFT21 or STED22,23, which may often require imaging fixed samples. The central task is the detection and estimation of diffraction-limited peaks emanating from single-molecules. Hence, providing adequate assumptions such as handling a constant positional accuracy instead of Brownian motion, MTT is straightforwardly suited for nanoscopic analyses. Furthermore, MTT can fundamentally be used at any scale: not only for molecules, but also for cells or animals, for instance. Hence, MTT is a powerful tracking algorithm that finds applications at molecular and cellular scales.

Institutions: University of Toronto, University of Toronto, University of Regina.

Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10.
Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.

Institutions: University of California, San Francisco , University of California, San Francisco , Queensland University of Technology, Brisbane, Australia.

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology1 even in complex tissue sections2. Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking.
Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells3, however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1).
We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

Bacterial cell division requires the coordinated assembly of more than ten essential proteins at midcell1,2. Central to this process is the formation of a ring-like suprastructure (Z-ring) by the FtsZ protein at the division plan3,4. The Z-ring consists of multiple single-stranded FtsZ protofilaments, and understanding the arrangement of the protofilaments inside the Z-ring will provide insight into the mechanism of Z-ring assembly and its function as a force generator5,6. This information has remained elusive due to current limitations in conventional fluorescence microscopy and electron microscopy. Conventional fluorescence microscopy is unable to provide a high-resolution image of the Z-ring due to the diffraction limit of light (~200 nm). Electron cryotomographic imaging has detected scattered FtsZ protofilaments in small C. crescentus cells7, but is difficult to apply to larger cells such as E. coli or B. subtilis. Here we describe the application of a super-resolution fluorescence microscopy method, Photoactivated Localization Microscopy (PALM), to quantitatively characterize the structural organization of the E. coli Z-ring8.
PALM imaging offers both high spatial resolution (~35 nm) and specific labeling to enable unambiguous identification of target proteins. We labeled FtsZ with the photoactivatable fluorescent protein mEos2, which switches from green fluorescence (excitation = 488 nm) to red fluorescence (excitation = 561 nm) upon activation at 405 nm9. During a PALM experiment, single FtsZ-mEos2 molecules are stochastically activated and the corresponding centroid positions of the single molecules are determined with <20 nm precision. A super-resolution image of the Z-ring is then reconstructed by superimposing the centroid positions of all detected FtsZ-mEos2 molecules.
Using this method, we found that the Z-ring has a fixed width of ~100 nm and is composed of a loose bundle of FtsZ protofilaments that overlap with each other in three dimensions. These data provide a springboard for further investigations of the cell cycle dependent changes of the Z-ring10 and can be applied to other proteins of interest.

It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission1-3. An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data4.
Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling.
The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an automatic module. Trajectory segmentation5 involves the identification of indoor and outdoor parts from pre-processed space-time tracks. Again, both interactive visual segmentation and automatic segmentation are supported. Segmented space-time tracks are then analyzed to derive characteristics of one's activity space such as activity radius etc. Density estimation and visualization are used to examine large amount of trajectory data to model hot spots and interactions. We demonstrate both density surface mapping6 and density volume rendering7. We also include a couple of other exploratory data analyses (EDA) and visualizations tools, such as Google Earth animation support and connection analysis. The suite of analytical as well as visual methods presented in this paper may be applied to any trajectory data for space-time activity studies.

The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.

Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls.
DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels.
In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.

This video demonstrates the preparation of an ultra-thin matrix/analyte layer for analyzing peptides and proteins by Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS) 1,2. The ultra-thin layer method involves the production of a substrate layer of matrix crystals (alpha-cyano-4-hydroxycinnamic acid) on the sample plate, which serves as a seeding ground for subsequent crystallization of a matrix/analyte mixture. Advantages of the ultra-thin layer method over other sample deposition approaches (e.g. dried droplet) are that it provides (i) greater tolerance to impurities such as salts and detergents, (ii) better resolution, and (iii) higher spatial uniformity. This method is especially useful for the accurate mass determination of proteins. The protocol was initially developed and optimized for the analysis of membrane proteins and used to successfully analyze ion channels, metabolite transporters, and receptors, containing between 2 and 12 transmembrane domains 2. Since the original publication, it has also shown to be equally useful for the analysis of soluble proteins. Indeed, we have used it for a large number of proteins having a wide range of properties, including those with molecular masses as high as 380 kDa 3. It is currently our method of choice for the molecular mass analysis of all proteins. The described procedure consistently produces high-quality spectra, and it is sensitive, robust, and easy to implement.

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